Skill UI

This skill provides systematic patterns and best practices for transforming slow database queries into high-performance operations. It covers techniques like proper indexing, query plan analysis (e.g., using EXPLAIN), schema design improvements, and resolving common issues like N+1 query problems. Use it to debug performance bottlenecks, reduce database load, and ensure scalable application backends.

A comprehensive guide detailing the most common and critical mistakes when developing with Supabase. Covers severe security issues (like exposing service role keys or missing RLS), data integrity failures, and performance bottlenecks (connection pooling, N+1 queries). Essential for code review, onboarding new developers, or auditing existing Supabase projects to ensure secure and robust applications.

This comprehensive profiler provides systematic performance analysis for modern applications built with Node.js, Python, and Go. It detects critical bottlenecks across CPU, memory, and I/O dimensions. Key features include generating flamegraphs, analyzing bundle sizes, optimizing database queries (N+1 detection), and running rigorous load tests using k6 and Artillery. It mandates before-and-after measurements to ensure verifiable performance improvements.

This skill simulates a senior engineer's final, deep audit of an entire codebase before committing or pushing to a remote repository. It systematically checks for junk files, dead code, security vulnerabilities (secrets, injection flaws), and performance bottlenecks (N+1 queries). Use this pre-flight check before any major release or public deployment to ensure maximum code quality and production readiness.

A specialized review tool for identifying critical performance bottlenecks within Django applications. It focuses on validating issues such as N+1 queries, unbounded querysets, missing database indexes, and write loops. Use this when you suspect database slowdowns or memory exhaustion due to inefficient ORM usage, ensuring findings are provable and actionable.

Guides Odoo developers through search, browse, create, write, domain filters, relational and computed field patterns, and performance-safe bulk operations while responding to @odoo-orm-expert prompts for idiomatic code and optimizations.

A comprehensive guide and methodology for identifying, measuring, and fixing performance bottlenecks across the entire stack. This skill covers optimizing database queries (e.g., N+1 problems, missing indexes), improving API efficiency (caching, parallel processing), and enhancing frontend performance (memoization, code splitting, image optimization). It emphasizes the critical 'Measure First' principle to ensure all optimizations are data-driven and effective.

A comprehensive guide for improving application speed across the entire stack, including frontend rendering, backend logic, and database queries. It outlines the crucial workflow—Measure, Identify, Fix, Verify—and addresses common bottlenecks like N+1 queries, Core Web Vitals improvements (LCP, INP, CLS), and large data handling.

This comprehensive guide covers best practices for building robust database systems. It teaches crucial concepts like schema normalization, effective indexing strategies, selecting the right database (e.g., SQLite vs PostgreSQL) and ORM, and optimizing queries to prevent common performance issues like N+1 problems. It emphasizes making context-aware architectural decisions.

This comprehensive guide outlines advanced strategies for optimizing interactions with the Attio REST API. Techniques covered include implementing LRU caching for schemas, using batch queries to avoid N+1 problems, efficient pagination (including streaming), and optimizing connection pooling via keep-alive. It helps developers maximize API throughput, minimize latency, and reliably process large volumes of data.

A comprehensive guide to optimizing API interactions with BambooHR. Learn advanced techniques like eliminating N+1 queries using custom reports, implementing incremental syncing with 'changed-since' endpoints, robust response caching (LRU/Redis), connection pooling, and request batching. Use this when facing slow API responses or needing high-throughput data synchronization.

This guide provides advanced strategies for optimizing interactions with the Notion API. Learn best practices such as implementing Time-To-Live (TTL) caching, batching multiple block updates, avoiding inefficient N+1 query patterns, and managing rate limits. Use this when your Notion application suffers from slow responses, high latency, or excessive API call consumption.